Triple
T35915654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthropic |
E1038740
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | AI safety research organization |
C425
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: AI safety research organization Context triple: [Anthropic, instanceOf, AI safety research organization]
-
A.
AI safety advocate
An AI safety advocate is a person who works to ensure artificial intelligence systems are developed, deployed, and governed in ways that minimize risks and harms while maximizing long-term benefits for humanity.
-
B.
machine learning research institute
A machine learning research institute is an organization dedicated to advancing the theory, algorithms, and applications of machine learning through systematic research, experimentation, and collaboration.
-
C.
AI research tool
An AI research tool is a software system that leverages artificial intelligence techniques to assist in discovering, organizing, analyzing, and generating scientific knowledge and insights.
-
D.
Allen Institute for Artificial Intelligence project
An Allen Institute for Artificial Intelligence project is a research or engineering initiative undertaken by AI2 to advance artificial intelligence through impactful, open, and often collaborative scientific and technological contributions.
-
E.
research and development organization
chosen
A research and development organization is an entity dedicated to systematically investigating ideas and technologies to create new knowledge, products, or processes and improve existing ones.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:07 p.m.